In the emerging era of Internet of Things (IoT), fog computing plays a critical role in serving delay-sensitive and location-aware applications. As a result, fog nodes are envisioned to be heavily deployed and form future distributed data centers. Powering fog nodes with green energy sources (such as solar and wind), not only helps in environmental and CO2 emission control but also paves the way towards a “sustainable IoT technology”. However, the downside of green energy is its variation and unpredictability, which needs to be engineered. In this paper, we use the Lyapunov optimization technique to derive algorithms for dynamic dispatching of the users’ requests among the nearby fog nodes and remote data centers. The proposed algorithms take into account the time constraints of the requests and maintain the system stability while efficiently utilize the available green energy sources. Exhaustive simulation results, based on solar radiation data supplied by the Australian Bureau of Meteorology, confirm the efficiency of the proposed algorithms. In particular, in terms of service time, the number of deadline misses and green energy utilization, the proposed algorithms outperform the state-of-the-art alternative up to 6%, 17% and 12%, respectively.
- Fog computing
- Lyapunov optimization technique
- Renewable energy
- Request dispatching
- Virtual queue